投稿時間:2022-01-14 10:24:59 RSSフィード2022-01-14 10:00 分まとめ(29件)

カテゴリー等	サイト名等	記事タイトル・トレンドワード等	リンクURL	頻出ワード・要約等/検索ボリューム	登録日
IT	気になる、記になる…	｢Baby Shark (サメのかぞく)｣がYouTube史上初の100億回再生を突破	https://taisy0.com/2022/01/14/150752.html	babysha	2022-01-14 00:33:00
IT	ITmedia 総合記事一覧	[ITmedia News] “早すぎたメタバース”「Second Life」のLinden Labに創業者が再参加	https://www.itmedia.co.jp/news/articles/2201/14/news074.html	itmedia	2022-01-14 09:50:00
IT	ITmedia 総合記事一覧	[ITmedia ビジネスオンライン] シティホテル「コートヤード・バイ・マリオット名古屋」開業　3月1日から	https://www.itmedia.co.jp/business/articles/2201/14/news060.html	itmedia	2022-01-14 09:35:00
TECH	Techable（テッカブル）	電話番号を使ったお手軽eコマースシステム「テレAI」誕生。“声”で注文するという原点回帰	https://techable.jp/archives/170704	会員登録	2022-01-14 00:00:26
AWS	AWS	AWS Training & Certification Skills Guild | Amazon Web Services	https://www.youtube.com/watch?v=Zq1dPbM_dnk	AWS Training amp Certification Skills Guild Amazon Web ServicesThis is a min video overview of AWS T amp C Skills Guild a comprehensive skills enablement program that builds cloud fluency across your organization AWS Skills Guild is a programmatic approach that helps you accelerate cloud outcomes by creating excitement increasing employee engagement and nurturing a culture of learning If you are interested in learning more about Skills Guild please visit or contact one of your AWS representatives Subscribe More AWS videos More AWS events videos ABOUT AWSAmazon Web Services AWS is the world s most comprehensive and broadly adopted cloud platform offering over fully featured services from data centers globally Millions of customers ーincluding the fastest growing startups largest enterprises and leading government agencies ーare using AWS to lower costs become more agile and innovate faster AWS AmazonWebServices CloudComputing	2022-01-14 00:20:54
AWS	AWS	Equipment Health & Maintenance on AWS | Amazon Web Services	https://www.youtube.com/watch?v=JLb4VumsFDc	Equipment Health amp Maintenance on AWS Amazon Web ServicesThe Equipment Health Maintenance solution is a cloud native offering that is built off of the AWS Refinery Monitoring Surveillance solution The solution provides predictive equipment analytics to improve operational insights and help customers drive equipment optimization and proactive maintenance planning The solution is a standardized approach that can scale to accommodate any selected equipment and potential workload within a downstream customer s environment Learn more about AWS Subscribe More AWS videos More AWS events videos ABOUT AWSAmazon Web Services AWS is the world s most comprehensive and broadly adopted cloud platform offering over fully featured services from data centers globally Millions of customers ーincluding the fastest growing startups largest enterprises and leading government agencies ーare using AWS to lower costs become more agile and innovate faster AWS AmazonWebServices CloudComputing Energy	2022-01-14 00:17:03
AWS	lambdaタグが付けられた新着投稿 - Qiita	Lambdaでrds自動起動停止	https://qiita.com/ry0_/items/cac2066e96e940f27417		2022-01-14 09:14:15
デザイン	コリス	これはかなりオススメの良書！ 最近のWebデザインのアイデア・作り方がよく分かる -Webデザイン良質見本帳	https://coliss.com/articles/book-review/isbn-9784815609092.html	続きを読む	2022-01-14 00:36:48
AWS	AWSタグが付けられた新着投稿 - Qiita	Lambdaでrds自動起動停止	https://qiita.com/ry0_/items/cac2066e96e940f27417		2022-01-14 09:14:15
Ruby	Railsタグが付けられた新着投稿 - Qiita	カラム型の種類	https://qiita.com/miya24/items/eb75a1818b9a1b36089c	bigint	2022-01-14 09:46:56
技術ブログ	Developers.IO	S3で静的WEBサイトを立ち上げようとしたら４０３（４０４）エラーが出て困った話	https://dev.classmethod.jp/articles/saitchan-20210114/	cloudfront	2022-01-14 00:39:04
海外TECH	DEV Community	How AI is used for mental health therapy	https://dev.to/mage_ai/how-ai-is-used-for-mental-health-therapy-59m6	How AI is used for mental health therapy TLDRAs the current mental health screening system relies too heavily on manual assessments how can sentiment analysis SA be used to streamline the new patient screening process and reduce the abysmal week long waitlist to receive help from a therapist OutlineThe issueWhat s all this jargon New patient debriefCTRL F for symptomsFurther research and considerationsConclusion The issueFor a generation of young people who have de stigmatized mental illness we are shocked to discover that finding a therapist is as appalling as our dating culture an arduous ghosting game Patients wait an average of weeks to see a mental health professional just to receive a diagnosis So if you are absolutely thirsty for attention then there are apps commonly sponsored by YouTubers that match you with a therapist but results may vary Why is it so difficult to receive help Since we rely solely on a mental health professional to review tens of pages of medical history and questionnaires for each new patient and with the normalization of mental illness the supply of qualified mental health professionals cannot keep up with the volume of patients seeking help It s alarming that while of people are mentally ill at any given time only get help and of therapists are exhausted and can t get up Life alert meme Treatment planSo how can machine learning help in this situation In this blog post we ll be exploring how a method of sentiment analysis named entity recognition NER can expedite the new patient screening process for psychologists by categorizing and summarizing large amounts of unwritten responses by patients This is a powerful information extraction tool that can potentially organize and make sense of otherwise unstructured and qualitative data that we currently rely on extremely specialized manual labor for Sentiment analysis in therapy is a very new area of study and the goal is not to replace mental health professionals but make their jobs easier using machine learning applications I genuinely hope there is more research in medicine and mental health so that we can not only ease the burden of overworked psychologists dealing with everyone s Zoom fatigue but also improve accessibility to mental healthcare for those in need Source What s all this jargon Before we discuss any AI I d like to spend some time addressing any confusion about the terms I just rattled off Sentiment analysisSentiment analysis SA is the way AI is able to extract human emotions and intensity through natural language processing and context Machine learning pipelineThe end goal of ML is to teach the model to do a task for you Suppose you are a weeb and want to learn Japanese did I just expose myself Doki Doki Literature Club referenceI like to think of sentiment analysis SA in machine learning akin to learning Japanese from watching hours of anime training stage then going to an authentic Japanese restaurant to eavesdrop on some people speaking Japanese testing stage Although you can t understand entire statements you used named entity recognition NER to pick up key phrases in the “PEOPLE category entity like mother in law husband and “unreasonable and that gives us a general vibe or sentiment that they re likely talking Named entity recognitionNER is actually an information extraction algorithm that trains itself on specialized jargon and then categorizes data into pre labeled entities or concepts Now that we have a better idea of what SA and NER are let s see how named entity recognition is useful for psychoanalysis New patient debriefUsing NER therapists can quickly familiarize themselves with new patients and which intense emotions they feel behaviors they exhibit which mental illness they suspect they have using the keywords patients used in their questionnaires Take this existing implementation of NER on identifying clinical terms in patient charts by John Snow Labs screenshot of demo below for example the ML model is able to identify symptoms of illness and treatment methods after learning medical jargon from the PubMD data set NER clinical demoThus for therapists instead of reading a patient s entire life story a sentence like this “When I m feeling anxious I overthink and lose my appetite Would be reduced to anxious B ILLNESSlose B SYMPTOMmy I SYMPTOMappetite I SYMPTOMSince some ideas are multiple words long we use the “B tag in front of the entity to indicate the first word in the phrase and those that follow after with the “I tag ImpactThis summary is significant in automating a time consuming step by allowing therapists to quickly grasp what s ailing the new patient Particularly for patients that require care from both a psychiatrist and therapist it would be revolutionary to have a tool that ensures communication between the medical professionals are concise detailed and missing no information A technical explanation of NERIf you are the godsend thinking of implementing a sentiment analysis using NER for therapists thank you and please refer to SnowLab s implementation and Medium article as a guide Else we can get a general idea of how this NER model by Spark NLP an open source Natural Language Processing library works through the same weeb analogy Since you cannot possibly learn Japanese from raw anime episodes someone has to do the manual labor of adding English subtitles before you watch it Therefore we have to convert sentences into a format the NER model understands CoNLL So my sentence “When I am feeling anxious I overthink and lose my appetite has punctuation removed and contractions like “I m expanded parts of speech tags added and is converted into this mess If you re kind of confused yet curious you can find the list for part of speech abbreviations here and try this example for yourself using my code snippet Essentially what s happening in the code is that we need to separate sentences into individual words mark their part of speech and entity labels like in this excerpt using “Paraiso from carbon now shFortunately the Spark NLP library has a couple built in functions that convert sentences into this format so you don t need to use the NLTK one I used in my example The functions are this tokenizer for converting sentences into individual words and a POS tagger for identifying part of speech But since they do not have entity labels for psychology terms like the “emotion and “behavior tags I used in my example we d need to find a library based on the The Diagnostic and Statistical Manual of Mental Disorders DSM that ll be used to identify mental illnesses and their symptoms in a piece of text Finally now that the training data is pre processed data scientists can now train the model test it and let therapists use it Let me know when it happens draw an owl meme CTRL F for symptomsOr CMD F for you Mac users On the other hand after identifying the symptoms emotions and behaviors of the patient from their questionnaire we can do a reverse search to look for more specific information Let s say the therapist noticed a patient used sleeping medication and wanted more context and why In SnowLab s implementation for example they wrote a search function called get clinical entities that finds all mentions of medications for patients as well as specifications if any about the quantity and frequency the medication is consumed The location of the sentence in the overall piece is also recorded to locate the information easier from line of NER clinical ApplicationsOnce this information is identified therapists can request data scientists to help them analyze and visualize trends in patient medical histories and whether treatments are effective or not For example a potential usage of analyzing a patient s medication history for psychiatrists is monitoring whether the medicine they re taking has improved their condition It would be a lot to keep track of the condition of the numerous psychiatric patients how dosages of several medications affect them and whether there are unexpected side effects over time but detecting anomalies and finding trends is what machine learning is great at Moreover if certain medication is proven to be successful for a statistically significant number of patients with ADHD who experience the symptoms “x y and z it is crucial that this discovery is shared with a medical professional While additional research is required ML can expedite this cross referencing process for psychiatrists One possible application is an attempt at unbiased data reporting by generating a list of ADHD patients taking this medication detailing whether they ve recovered or not the duration of consumption and the side effects they experienced Further research and considerationsThere are many more ways sentiment analysis would improve the quality of therapy and assist mental health professionals in treating more patients In addition to the ways textual information extraction SAs determine emotion in unstructured self reported medical reports other forms of sentiment analysis could improve other facets of mental healthcare such as A classifier based on various parameters describing patient condition of whether a patient could be in a bad mental state and harm themselves A support vector machine SVM is allegedly one of the best ML approaches that predict the polarity of a sentiment according to the rd reference “Emotion AI Driven Sentiment Analysis Somehow quantifying a severity score of a patient s condition to indicate they re in critical condition and get them help fasterDue to the personalized nature of therapy it can also be difficult to get definitive feedback from patients In this study researchers have been trying to identify which words exchanged between therapist and patient were most effective at treating their illness using natural language processing NLP This is the umbrella sentiment analysis falls underHow to normalize qualitative data like subjective description of emotions so that a patient who describes their emotions more animatedly does not receive a biased score over a patient who keeps things to themselves ConclusionWhether you are a medical professional data scientist or someone with an interest I thank you for taking the time to consider all of these ways sentiment analysis can benefit therapy I believe your work and contribution to research in using machine learning to improve the quality of healthcare is noble and greatly appreciated in these times when we re experiencing a mental health crisis and a shortage in healthcare workers capoo I m grateful that the two most important people in my life have access to mental healthcare and I hope that with further interdisciplinary research this accessibility is extended to more people s loved ones	2022-01-14 00:43:29
海外TECH	Engadget	Meta's Spanish-language moderators have reportedly been working in unsafe conditions	https://www.engadget.com/meta-genpact-spanish-langauge-descrimination-001938677.html?src=rss	Meta x s Spanish language moderators have reportedly been working in unsafe conditionsIt s no secret Meta employs contract laborers to do much of the hard work of enforcing its content moderation policies And despite assisting one of the most valuable companies in the world those workers have frequently complained of their jobs involving poor compensation and anxiety inducing work Some are now also saying they re being treated worse than other workers According to BuzzFeed News Genpact a Meta subcontractor that has previously been accused of fostering poor working conditions has required the Spanish language moderators out of its Richardson Texas office to report for in person work since April Those workers have had to put their health at risk against both the delta and omicron coronavirus variants while their English language counterparts have been allowed to cycle through the office in three month rotations The news of the situation at Genpact comes just one week after workers at Accenture another Meta subcontractor successfully protested to force the company to scrap a requirement it had in place for hundreds of Facebook moderators to return to in person work on January th Contractors who spoke to BuzzFeed News claim Genpact also holds them to unreasonable standards They say they re expected to make moderation decisions in about a minute while maintaining an percent accuracy rate Complicating everything is the fact that Meta reportedly doesn t disseminate guidelines on how to apply Facebook s Community Standards in a language other than English leaving those workers in a situation where they re forced to first translate that guidance before applying it nbsp And there s the scale of the problem the team has to tackle Genpact s Spanish language moderation team is named after Mexico but in addition to moderating content posted by people living in the North American country they re also responsible for Facebook and Instagram posts from Spanish speaking users in most Latin American countries as well In Mexico alone Facebook has more than million users By contrast the Genpact Mexican market team consists of approximately individuals “We use the combination of technology and people to keep content that breaks our rules off of our platform and while AI has made progress in this space people are a key part of our safety efforts a Meta spokesperson told Engadget “We know these jobs can be difficult which is why we work closely with our partners to constantly evaluate how to best support these teams	2022-01-14 00:19:38
海外TECH	CodeProject Latest Articles	Harlinn.Windows - A Visual Studio 2022 Solution	https://www.codeproject.com/Articles/5319700/Harlinn-Windows-A-Visual-Studio-2022-Solution	harlinn	2022-01-14 00:23:00
海外科学	NYT > Science	Patient in Groundbreaking Pig Heart Transplant Has a Criminal Record	https://www.nytimes.com/2022/01/13/health/pig-heart-transplant-bennett.html	Patient in Groundbreaking Pig Heart Transplant Has a Criminal RecordDavid Bennett Sr was involved in a serious assault nearly years ago court records show Such histories should not disqualify patients his doctors said	2022-01-14 00:02:19
海外ニュース	Japan Times latest articles	Russia, at an impasse with the West, warns it is ready to abandon diplomacy	https://www.japantimes.co.jp/news/2022/01/14/world/politics-diplomacy-world/russia-ukraine-nato/	ukraine	2022-01-14 09:38:23
海外ニュース	Japan Times latest articles	Former Prime Minister Toshiki Kaifu dies at 91	https://www.japantimes.co.jp/news/2022/01/14/national/politics-diplomacy/toshiki-kaifu-obituary/	november	2022-01-14 09:29:09
海外ニュース	Japan Times latest articles	The Tokyo Bar Association needs our help to understand racial profiling in Japan	https://www.japantimes.co.jp/community/2022/01/14/our-lives/tokyo-bar-association-survey-on-racial-profiling-by-police-in-japan/	The Tokyo Bar Association needs our help to understand racial profiling in JapanThe Tokyo Bar Association has put together a multilingual questionnaire to try and find answers on how suspected racial profiling affects the non Japanese community	2022-01-14 09:30:11
海外ニュース	Japan Times latest articles	Language roars to life in 2022, the Year of the Tiger	https://www.japantimes.co.jp/life/2022/01/14/language/japanese-language-roars-to-life-in-2022-the-year-of-the-tiger/	moment	2022-01-14 09:30:05
ニュース	BBC News - Home	Prince Andrew: Why the military titles and royal patronages meant so much	https://www.bbc.co.uk/news/uk-59989886?at_medium=RSS&at_campaign=KARANGA	patronages	2022-01-14 00:06:28
ニュース	BBC News - Home	Google will spend £730m to 'reinvigorate' its UK offices	https://www.bbc.co.uk/news/business-59980216?at_medium=RSS&at_campaign=KARANGA	environment	2022-01-14 00:01:57
ニュース	BBC News - Home	Racism in cricket: Government should limit public funding unless progress is made - DCMS report	https://www.bbc.co.uk/sport/cricket/59981141?at_medium=RSS&at_campaign=KARANGA	Racism in cricket Government should limit public funding unless progress is made DCMS reportThe government should limit public funding for cricket unless there is continuous demonstrable progress on eradicating racism a parliamentary report says	2022-01-14 00:01:20
ニュース	BBC News - Home	NI police 'did not warn murder victims about threats'	https://www.bbc.co.uk/news/uk-northern-ireland-59984500?at_medium=RSS&at_campaign=KARANGA	troubles	2022-01-14 00:01:36
ニュース	BBC News - Home	Don't use refund firms to claim tax rebates, says Which?	https://www.bbc.co.uk/news/business-59980217?at_medium=RSS&at_campaign=KARANGA	hundreds	2022-01-14 00:02:25
ニュース	BBC News - Home	The papers: Prince Andrew 'throne out' as Queen strips his titles	https://www.bbc.co.uk/news/blogs-the-papers-59989736?at_medium=RSS&at_campaign=KARANGA	front	2022-01-14 00:41:12
ビジネス	ダイヤモンド・オンライン - 新着記事	米最高裁によるワクチン接種義務化差し止め、企業の反応割れる - WSJ発	https://diamond.jp/articles/-/293320	義務	2022-01-14 09:07:00
北海道	北海道新聞	堀島と川村が２位、Ｗ杯モーグル　杉本３位	https://www.hokkaido-np.co.jp/article/633211/	杉本	2022-01-14 09:03:12
北海道	北海道新聞	海部俊樹元首相が死去　９１歳	https://www.hokkaido-np.co.jp/article/633215/	海部俊樹	2022-01-14 09:09:00
北海道	北海道新聞	川重製車両の運転再開凍結　ワシントン首都圏地下鉄	https://www.hokkaido-np.co.jp/article/633216/	運転再開	2022-01-14 09:09:00